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ISCSLP2024 Conversational Voice Clone Challenge(CoVoC) baseline model.
There are two baseline models in this competition.
VALL-E:
VALL-E is trained using Amphion.
First, training is performed on the Wenetspeech4TTS dataset, and the model weight is valle_base_model.bin.
After that, fine-tuning is performed on the HQ-Conversations dataset, the model weight is valle_HQ-sft_model.bin.
For specific inference code, please refer to ISCSLP2024_CoVoC_baseline Github for more details.
fish-speech:
An open-source speech model, fish-speech, whose LLAMA and vits_decoder are fine-tuned using the HQ-Conversations dataset.
The training follows the default configuration of fish-speech.
For specific training code, please refer to Fish Speech Github for more details.